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A new method for supervised hyperspectral data classification is proposed. In particular, the notion of Stochastic Minimum Spanning Forests (MSFs) is introduced. For a given hyperspectral image, a pixelwise classification is first performed. From this classification map, M marker maps are generated by randomly selecting pixels and labeling them as markers for the construction of MSFs. The next step consists in building an MSF from each of the M marker maps. Finally, all the M realizations aredoi:10.1109/icip.2011.6115664 dblp:conf/icip/BernardTACB11 fatcat:3cthjmswtrfojho5dxmsizvguu